Predicting the Success Rate before Liver Transplant using ANN

  • Gupta A
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Abstract

The counterfeit learning models, for example, the artificial neural system, radial basis function and art map have demonstrated a promising application in the medicinal industry. The present work is a comparative examination of the previously mentioned. The consequences of our examination have demonstrated that among Artificial neural system, radial basis function and art map the numeric qualities acquired from ANN were relatively better. Further, the investigation of the exactness among the three chose calculations was found 98.9708%, 97.2556%, and 58.1475% separately. As per writing overview performed, it is clear that most examinations right now got lesser consideration, particularly in India. In view of our discoveries it appears that the ANN could be the best mode to predict the joint stabilities during liver transplantation.

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Gupta, A. (2020). Predicting the Success Rate before Liver Transplant using ANN. International Journal of Innovative Technology and Exploring Engineering, 9(5), 1872–1876. https://doi.org/10.35940/ijitee.e2837.039520

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